Early Experience of COVID-19 in a US Children's Hospital.

OBJECTIVES: We aim to describe the demographics, clinical presentation, hospital course, and severity of pediatric inpatients with coronavirus disease 2019 (COVID-19), with an emphasis on healthy, immunocompromised, and chronically ill children. METHODS: We conducted a single-center retrospective cohort study of hospitalized children aged younger than 22 years with COVID-19 infection at Steven and Alexandra Cohen Children's Medical Center at Northwell Health. Cases were identified from patients with fever and/or respiratory symptoms who underwent a nucleic acid amplification-based test for severe acute respiratory syndrome coronavirus 2. RESULTS: Sixty-five patients were identified. The median age was 10.3 years (interquartile range, 1.4 months to 16.3 years), with 48% of patients older than 12 years and 29% of patients younger than 60 days of age. Fever was present in 86% of patients, lower respiratory symptoms or signs in 60%, and gastrointestinal symptoms in 62%. Thirty-five percent of patients required ICU care. The white blood cell count was elevated in severe disease (P = .0027), as was the C-reactive protein level (P = .0192), compared with mild and moderate disease. Respiratory support was required in 34% of patients. Severity was lowest in infants younger than 60 days of age and highest in chronically ill children; 79% of immunocompromised children had mild disease. One death was reported. CONCLUSIONS: Among children who are hospitalized for COVID-19, most are younger than 60 days or older than 12 years of age. Children may have severe infection requiring intensive care support. The clinical course of immunocompromised patients was not more severe than that of other children. Elevated white blood cell count and C-reactive protein level are associated with greater illness severity.

The need to serve rural america.

Biologics and the new diagnostics are needed in rural areas nationwide.

Is disease management right for oncology?

The disease management (DM) model for the treatment of chronic conditions has been around for many years and has been found to be effective for diseases of high prevalence and high cost (eg, diabetes, asthma, heart disease). With an increasing number of people living with cancer and the continual escalation of treatment costs, DM vendors have begun to implement DM concepts into cancer care. However, the multitude of cancer types, treatment options, and adverse effects have all presented barriers to oncology DM, and data reflecting the effectiveness of oncology DM have remained scarce. Oncology costs, the lack of congruence between provider and patient expectations of treatment, the lack of prevention and early detection for many cancers, and, most importantly, the inability of people to adhere to healthy lifestyles are additional obstacles that must be overcome. Moreover, when designing an oncology DM program, it is imperative to look at cancers individually as the etiology, treatment, and impact of cancer can be markedly different from one patient to the next. An effective oncology DM program is one that acts to decrease fatigue, reduces nosocomial infections, deals with dehydration and pain, manages anemia, identifies and treats skin infections, recognizes and treats depression and other psychological distress, provides patients access to palliative care services, facilitates informed decision making and end-of-life transitions, and promotes communication between patients and their providers as well as between physicians. Moving forward, DM vendors and health insurance companies capable of incorporating DM with medical management will be in the best position to provide optimal cancer care.

High rates of inappropriate drug use in the chronic pain population.

Chronic opioid treatment is a highly effective method to treat chronic pain; however, the prevalence of abuse of opioids can make treating patients with these agents difficult for clinicians. The objective of this study was to describe rates of inappropriate utilization, abuse, and diversion in a population of patients who were prescribed chronic opioids, as measured by urine drug testing in the clinical setting. A retrospective analysis was conducted of results from all urine drug tests conducted by Ameritox, Ltd. between January 2006 and January 2009, for patients whose physicians ordered the test in order to screen for noncompliance. Data from 938,586 patient test samples showed that 75% of patients were unlikely to be taking their medications in a manner consistent with their prescribed pain regimen. Thirty-eight percent of patients were found to have no detectable level of their prescribed medication, 29% had a nonprescribed medication present, 27% had a drug level higher than expected, 15% had a drug level lower than expected, and 11% had illicit drugs detected in their urine. Note that all categories add to a total greater than 100% as each category is not mutually exclusive, and a single patient could fall into multiple categories. The high observed rate of noncompliance demonstrates a significant clinical concern and confirms the importance of periodic urine drug screening for the population prescribed long-term opioid therapy.